Gartner recently predicted that Business Intelligence (BI) and Analytics will remain a top focus for CIOs through 2017. As the benefits of a data-driven decision-making process become more evident, we’ll see most businesses adopt a BI strategy in one form or another over the next few years.

The only problem: Many businesses still don’t quite understand BI. They have a general idea, but the concept remains clouded in misconceptions. These misconceptions keep many businesses from adopting BI, or from taking full advantage of its potential.

Today, I’d like to address these misconceptions, and explain why they’re false. So, what are the biggest areas of confusion surrounding BI? While the list could be much larger, here are 9 of the most common BI misconceptions:

1. BI doesn’t have value

While fading, this misconception is still alive and well among a small minority of business leaders. It’s to be expected. Many people are quick to dismiss a trend without first understanding its value. Don’t make that mistake with BI. As data plays an increasingly larger role in business, ignoring BI will put your company at a competitive disadvantage. As mentioned below, don’t dismiss it until you truly understand its potential.

“I believe the biggest misconception of BI by CEO’s is the belief that it doesn’t have value,” says Steve Cross, CEO of Infinite Synergy. “Just like anything in life, if people don’t understand something they are quick to either fear or dismiss it.”

2. BI is only for (fill in the blank) organizations with (fill in the blank)

“Business Intelligence is only for big organizations with big budgets.”
“BI is only for technology companies with lots of data.”
“It’s only for (fill in the blank) organizations with (fill in the blank).”
These are all common misconceptions that businesses use to rationalize their avoidance of BI. Are any of these statements accurate? Nope. These days, any business that has data can use Business Intelligence.

“Every organization can embrace effective BI targets regardless of size, budgets or tenure,” explains Sara Handel, Business Intelligence Services Lead at Excella Consulting. “Every organization today collects or uses data in some fashion and can track data that is important to them in order to make effective decisions. While you may not be ready for a comprehensive tool, you can start with Excel and Google analytics and expand as your organization grows.”

3. Measuring data = successful BI

Many companies measure data. Few actually use BI successfully. For instance, many business leaders look over the numbers every day and assume they’re using BI. But, unless that data drives action, they’re measuring vanity metrics–data that makes them feel nice, but doesn’t lead to change.

“Many businesses think that creating reports and reviewing the numbers is enough,” explains Handel. “True BI uses data, collected from different sources and analyzed in different ways, to make informed decisions over time. If you are just running the same report and looking at the same numbers but aren’t actually using that information to make decisions or alter your strategies, then you aren’t doing BI.”

4. BI = reports and dashboards

BI isn’t about sending a report to an executive on a daily basis. It’s not about giving them a dashboard. It’s about giving them the tools and resources needed to get the right information when they need it most. Sure, that could involve reports and/or dashboards, but the point is this: BI shouldn’t be limited by location, device, or time. If an executive needs sales numbers for the past month while walking into a meeting halfway around the world, he/she should be able to get them instantly.

“Despite the fact that reports and dashboards are standard tools of a classical BI, they do not define the value by themselves” says Sergii Shelpuk, Data Science Group Director, SoftServe. “BI is a solution for delivering the right information to the right people at the right time. Business needs go first and specific tools for delivering such information should be picked after defining: what is the right information, who are the right people and when is the right time.”

5. More data = better BI

“This is flat out wrong,” says Anita Andrews, VP, Client Analytics Services at RJMetrics. “The larger community is so quantity obsessed (of course it’s fun for some to solve the computational and processing problems associated with massive data sets), but it’s actually the case that if you can double your revenue with one column of data, you’d do it in a heartbeat.”

With business intelligence, everything starts and ends with data quality–not quantity. Don’t try to measure every piece of data possible. You’ll only overwhelm yourself. Instead, focus your efforts on the data that matters. Make sure it’s accessible, accurate, and reliable. Without data quality, you can’t hope to accomplish anything with BI.

6. All BI tools are the same

This misconception leads to disastrous consequences. Based on this flawed assumption, some businesses choose their BI tool based on popularity, not on business requirements. They assume that the most-hyped solution must be the best solution for them. This is a dangerous assumption.

The fact is, every BI solution is different. They’re built on different architecture. They offer different security features. They offer different capabilities. As explained below, the popular solution may not be the best fit for your company.

“When it comes to BI, one size doesn’t fit all,” says Takashi Binns, Senior Manager, Solutions Delivery at arcplan. “The hype surrounding the most popular solution does not necessarily translate to value for your organization. Business teams must evaluate whether the solution is compatible with their data architecture, whether it will address their team’s specific requirements, and whether it is scalable for future development. Organizations set themselves up for failure when they solely buy into the hype of a BI tool. The best tool for your team just may be the underdog.”

7. We need ‘big data’ for BI to be meaningful

It seems like “Big Data” suffers from the same problem as HTML5: everyone wants it, but few actually know what it is. Many falsely associate BI with Big Data, assuming they need both to extract any value from their data. In reality, BI and Big Data are two separate things. Sure, they may overlap in some areas, but you certainly don’t need “big data” with your BI.

“Big data hype has done a great thing – it has emphasized importance of integrating real-time and unstructured data into the decision-making process,” explains Binns. “But don’t get hung up on chasing big data as the only means of getting insight into your company’s operations. Your company may not even have – and may never have a need for – big data. Business leaders can glean insight into business operations by performing various analytic techniques on their regular data to improve business processes, efficiency and profitability.”

8. Business intelligence is an IT job

“Historically, running queries and generating reports for the business team were back-office activities assigned to the IT department,” says Binns. “With little communication between these two groups, obtaining valuable information was hit or miss. But organizations actually get the best value from BI when business and IT collaborate. Business leaders know what KPIs are most important, and the IT group has the technical acumen to assemble the right data using best practices. It takes communication between these two groups in order to achieve valuable business insight and yield a return on a BI software investment.”

I agree–proper BI requires collaboration between IT and the business, but I might even take that one step further. With modern BI solutions, business users can easily create their own analytic applications without even going through the IT department at all. Sure, IT still plays a role–they must control the data and user access–but they can now place much of the reporting duties in the hands of the users.

9. BI Software = BI Strategy

The term “Business Intelligence,” is largely associated with software. But, it’s much more than that. As mentioned in “The 4 P’s of Business Intelligence Success,” software is just one part of the BI implementation process. As explained below, successful BI projects requires internal changes as well–which are typically more difficult than implementing software.

“Some people make the mistake of assuming having Business Intelligence software and technology means they have a Business Intelligence strategy,” says James Ficarra & Adam Rene, Senior Project Managers & Engineers at ExcelAutomationHelp.com. “Nothing could be further from the truth. While the BI software should provide timely information to support decisions, these decisions are ultimately made by humans. In addition to software, a successful BI implementation must include systematic changes to an organization’s culture, making them more data-driven. Strong cultures are identified through strong patterns of accountability which encourage and reward data-driven decision making.”

So, what do you think? Would you add anything else to that list? If so, I’d love to hear your thoughts in the comments.